This report is an overview of the initial observations and analysis performed on the Food Security Cluster 5Ws data for 2021; the issues identified and analysis have been broken into large groups corresponding with the first 4 chapters – geographical coverage, activities and modalities, partners and beneficiaries. This report ends with a brief section on next steps and an interactive reference table and interactive reference maps.
We have endeavoured to provide actionable information and believe that releasing this report is a necessary part of jump-starting the process of resolving the more pressing concerns identified. Further analysis is merited in several areas; and this will be undertaken once consultations with partners have been completed.
Unless otherwise specified, beneficiary figures in this report are unique beneficiaries, as opposed to beneficiary frequencies.
A total of 3,260,968 unique beneficiaries have been reached across the country; this is 117.79% of the targetted 2,768,349 persons; however, not all the beneficiaries reached corresponded to areas where there were targets – this is explored in more detail in the section on townships.
| state | beneficiaries | %_of_ben | target | %_of_target | %_target_reached | PIN |
|---|---|---|---|---|---|---|
| Yangon | 2,011,575 | 61.83 | 1,777,522 | 64.21 | 113.17 | 1,777,522 |
| Rakhine | 530,202 | 16.30 | 487,182 | 17.60 | 108.83 | 632,805 |
| Mandalay | 143,526 | 4.41 | 381,818 | 13.79 | 37.59 | 381,818 |
| Ayeyarwady | 99,481 | 3.06 | 0 | 0.00 | 0 | |
| Magway | 96,767 | 2.97 | 0 | 0.00 | 0 | |
| Kachin | 89,818 | 2.76 | 86,117 | 3.11 | 104.30 | 102,649 |
| Kayin | 68,108 | 2.09 | 6,855 | 0.25 | 993.55 | 6,855 |
| Shan (North) | 66,220 | 2.04 | 13,428 | 0.49 | 493.15 | 24,657 |
| Mon | 48,181 | 1.48 | 0 | 0.00 | 0 | |
| Sagaing | 31,985 | 0.98 | 0 | 0.00 | 0 | |
| Kayah | 17,746 | 0.55 | 5,830 | 0.21 | 304.39 | 5,830 |
| Chin | 17,005 | 0.52 | 5,106 | 0.18 | 333.04 | 13,275 |
| Shan (South) | 15,511 | 0.48 | 1,978 | 0.07 | 784.18 | 2,054 |
| Bago (East) | 12,974 | 0.40 | 2,513 | 0.09 | 516.28 | 2,513 |
| Tanintharyi | 4,476 | 0.14 | 0 | 0.00 | 0 |
Yangon and Rakhine form both 82% of the target and 78% of the beneficiaries reached. Mandalay has has the largest difference between targets and beneficiaries reached. There were five states (Ayeyarwady, Mon, Sagaing, Magway and Tanintharyi) where beneficiaries were reached but were not included as part of the 2021 target or PIN; however, the beneficiaries reached in these areas represent less than 5% of all beneficiaries reached. Additionally, targets have been exceeded in all states except Mandalay, with Kayin having reached 994% of its target of 6,855 persons.
However, moving forward, the PIN for 2022 is much more evenly spread across the country: with reference to the plot below, Yangon, along with Magway and Mandalay have some of the lowest proportions of vulnerable persons in relation to the total state population, meaning that careful beneficiary selection and tight vulnerability in these areas will necessary to avoid excessive inclusion errors.
Just as the response is heavily weighted towards Yangon and Rakhine at the state and region level, the same is also true at the township level. These 10 townships below are where 76% of all FSC beneficiaries have been reached, they represent 60% of the 2021 target. In particular, Hlaingtharya has beneficiary figures that are 378% of its target. Additionally, neither Nyaung-U nor Myingyan were targetted as part of the 2021 PIN despite being in the top 10 townships by beneficiaries reached – 82.68% of beneficiaries reached corresponded to townships with targets.
| township | state | beneficiaries | %_of_ben | target | %_of_target | %reached |
|---|---|---|---|---|---|---|
| Hlaingtharya | Yangon | 772,658 | 23.69 | 204,542 | 9.32 | 377.75 |
| Shwepyithar | Yangon | 380,550 | 11.67 | 208,922 | 9.52 | 182.15 |
| Dagon Myothit (Seikkan) | Yangon | 276,430 | 8.48 | 199,242 | 9.08 | 138.74 |
| Dala | Yangon | 271,760 | 8.33 | 200,589 | 9.14 | 135.48 |
| North Okkalapa | Yangon | 255,380 | 7.83 | 190,909 | 8.70 | 133.77 |
| Sittwe | Rakhine | 149,885 | 4.60 | 127,750 | 5.82 | 117.33 |
| Buthidaung | Rakhine | 147,985 | 4.54 | 121,631 | 5.54 | 121.67 |
| Maungdaw | Rakhine | 121,432 | 3.72 | 71,360 | 3.25 | 170.17 |
| Nyaung-U | Mandalay | 71,547 | 2.19 | 0 | 0.00 | |
| Myingyan | Mandalay | 46,608 | 1.43 | 0 | 0.00 |
152 townships have been reached by food security activities in the first three-quarters of 2021. This is 42.7% the 330 townships in the country. It is also important to note that two townships – Hpapun in Kayin and Kyethi in Shan (South) have been targetted since the initial 2021 HRP, yet have not been reached by any FSC activities; 5 townships, overall, in either the HRP or IERP, have not benefitted from any FSC activities.
Overall, 97.4% of the targetted population was reached. From the histogram below, we can see that overreach and under-reaching were very common – townships are commonly clustered at around 0% reached and also at 200% reached or more. Of the 50 townships reached in 2021; 28 townships reached more than 120% of their target, 3 reached between 100% and 119% of their target; 4 townships reached between 80% and 100% of their target; and 15 townships reached less than 80% of their target.
Partners have responded in a total of 2500 locations across the country, with the vast majority of locations only having only one partner operating in them; the maximum number of partners in any location is 4. Of the 16041 rows reported in the 5Ws, only 211 did not report a specific location.
Locations are classified into three groups – camps, industrial zones and villages/towns/wards:
| location_type | locations | townships | beneficiaries | pc_of_ben | avg_ben_per_loc |
|---|---|---|---|---|---|
| village_ward_town | 2,088 | 125 | 2,546,522 | 88.45 | 1,220 |
| camp | 435 | 42 | 324,606 | 11.27 | 746 |
| industrial_zone | 5 | 2 | 7,870 | 0.27 | 1,574 |
The vast majority of locations are served by only one partner. Below are a series of histograms showing the variation in the number of beneficiaries by location, split by number of partners in each location. Locations with one partner present have a large peak around 100 beneficiaries per locations; and a slight majority of locations with two partners have more than 1,000 beneficiaries.
The more partners operating in a given location, the higher the average number of beneficiaries; however, it should be noted that these multi-partner locations are comparatively rare. The location with four partners is Nam Hlaing in Bhamo, Kachin.
| number_of_partners | locations | avg_beneficiaries |
|---|---|---|
| one | 2,396 | 142 |
| two | 110 | 930 |
| three | 12 | 2,258 |
| four | 1 | 49 |
Partners reported their achievements across the eight 5W activities. We see that the majority of the caseload for monthly cash-based transfers was established prior to 2021 (with the number of beneficiaries only increasing very incrementally across the course of the year) – this aligns with our understanding that many of the projects contributing to this activity were multi-year in nature and had been ongoing prior to the HRP; this pattern is also apparent in the provision of technical training.
One of the difficulties of interpreting these data is that it is not always apparent where the patterns observed are reflective or changes in the field (such as changes in access, funding or staffing) or if they are instead due to partners’ reporting behaviours. We note, for instance, a large jump in the number of beneficiaries for fishery kits and food baskets around July 2021 – this was due to the newly-approved addendum to the HRP. However, some of the other changes are less clear and will require careful exploration with partners.
Cash and in-kind distributions were each the main delivery modality in three activities, with the provision of services and support being predominant in two. The in-kind modality has the highest reach, given the especially large beneficiary numbers originating from the provision of monthly food baskets. We also note several misclassifications – small portions of monthly cash transfers have been coded as “in-kind” and there are in-kind food baskets coded as “cash” and “hybrid”. It might also be worth more clearly delineating between “support for income-generating activities” and the “provision of technical training” as service delivery and support are heavily present in both.
61% of beneficiary frequencies received support through the in-kind delivery modality; we use beneficiary frequencies here as there were several instances of modalities changing partway through an intervention: for reference, 83% of beneficiaries were reached initially with in-kind interventions, meaning that there was a tendency to diversify away from in-kind support over 2021. 25% of beneficiary frequencies were reached by cash transfers.
| delivery_modality | First | Monthly | One-off | Other | NA | Total | %Total |
|---|---|---|---|---|---|---|---|
| In-kind | 303,595 | 1,850,712 | 509,892 | 2,773,854 | 111,839 | 5,549,892 | 61.36 |
| Cash | 894 | 1,923,133 | 176,464 | 40,274 | 117,525 | 2,258,290 | 24.97 |
| Service delivery/support | 773,212 | 128,852 | 4,901 | 767 | 907,732 | 10.04 | |
| Hybrid (In-kind & Cash) | 295,312 | 2,938 | 10,810 | 309,060 | 3.42 | ||
| Voucher | 2,652 | 16,519 | 19,171 | 0.21 | |||
| Total | 304,489 | 4,842,369 | 820,798 | 2,846,358 | 230,131 | 9,044,145 | 100.00 |
Regarding the table above, there is a strong argument to remove the option “other” from the 5W column frequency (referring to frequency of transfer/delivery) – what exactly it connotes is unclear, as partners might elect this option for activities that occur both more and less frequently than every month; there is also the possibility that partners are just electing “other” instead of leaving the column blank. It is possible to backfill some of the “other” values from the beneficiary_recurrency column. This will be explored further in the chapter on beneficiaries.
There is also justification to drop the “First” category as it does not really have much relation to the “Monthly” category, i.e. an increase in beneficiaries reported as “First” do not correspond to an increase in “Monthly” beneficiaries in the following months, meaning that these beneficiaries should fall under the “One-off” category.
A key piece of missing information not currently captured by the 5W template is the duration of these activities – the number of months a monthly food basket is provided can only be calculated somewhat reliably with considerable effort. The table below shows the average duration (in months) of the various activities in the frequency category “Monthly”:
| activity | avg_duration_months |
|---|---|
| Provide monthly cash-based transfers | 7.38 |
| Provide crops & vegetables kits | 6.00 |
| Provide support for income generation | 5.99 |
| Provide technical training | 4.75 |
| Provide monthly food baskets | 4.24 |
| Cash for Work / Food for Assets | 2.13 |
The most common transfer values – in terms of beneficiaries reached – are between USD 10 and USD 20, though it should be noted that a not insignificant number of households (about 7%) were reached by cash transfer interventions valued at USD 100 per household or more. Please note that these monetary values were calculated only from rows with unique beneficiaries and that we are not using the cumulative sums per household.
| cash_delivery_mechanism | <$10 | >=$10_<$20 | >=$20_<$40 | >=$40_<$60 | >=$60_<$100 | >=$100_<$200 | >=$200 | total_hhd | pc_of_hhd |
|---|---|---|---|---|---|---|---|---|---|
| Direct cash payment | 6,901 | 21,224 | 5,967 | 8,792 | 4,759 | 2,655 | 230 | 50,528 | 84.03 |
| E-voucher | 2,519 | 929 | 3,448 | 5.73 | |||||
| E-transfer | 798 | 1,161 | 435 | 2,394 | 3.98 | ||||
| Mobile money | 1,830 | 1,830 | 3.04 | ||||||
| Money Transfer Agent | 517 | 90 | 841 | 1,448 | 2.41 | ||||
| Other | 8 | 403 | 21 | 432 | 0.72 | ||||
| Paper voucher | 48 | 48 | 0.08 |
by far the most common cash delivery mechanism was direct cash payments – 84.03% of beneficiaries were reached through this mechanism. Transfers made through Money transfer agents had the highest average transfer amount.
Next, let us take a look at household package values by activity type:
| activity | households | total_value_usd | avg_transfer_value |
|---|---|---|---|
| Provide livestock kits | 1,030 | 103,950 | 100.92 |
| Provide monthly cash-based transfers | 43,204 | 2,076,185 | 48.06 |
| Provide support for income generation | 11,584 | 420,000 | 36.26 |
| Cash for Work / Food for Assets | 22,298 | 785,768 | 35.24 |
| Provide crops & vegetables kits | 33,187 | 240,694 | 7.25 |
| Provide technical training | 45,296 | 221,821 | 4.90 |
| Provide fishery kits | 1,601 | 4,032 | 2.52 |
| Provide monthly food baskets | 672,804 | 291,859 | 0.43 |
Overall, the highest average cash transfers were from the provision of livestock kits and the lowest averages from fishery kits (after discounting food baskets, where less than 1% of activities reported the package value). It is also unclear if fishery kits and technical training tended to have particularly small cash components or if there were data entry errors. But the average package values are only part of the picture and significant variation in transfer values exists within each activity:
It would be fruitful to explore the provision of monthly cash-based transfers in more detail – this activity has a very clear peak at >=$10_<$20. A closer look reveals that this is almost entirely due to the 22,543 beneficiaries who received monthly transfers of USD 10.50/month (or MMK 15,000) per household. It is unclear whether this is a data entry error – but what we do know is that the households that received this type of transfer were not smaller than average; it might also be possible that this activity had been conceived as one singular transfer that had been split across several months.
This should be followed up with the 7 partners who provided this transfer value to beneficiary households; they are: WFP, Plan International, Save the Children, Myanmar Heart Development Organisation, People for People, World Vision Myanmar and People in Need.
This amount falls far below the minimum expenditure basket for food identified by the Cash Working Group, which established a floor of MMK 190,555 per household per month. Below is a table which summarises the percentage of the minimum expenditure basket for food which is covered by the different bins we have established for the cash-transfer values:
| usd_hhd_bin | avg_pc_of_meb | avg_usd_month | households | pc_of_hhd |
|---|---|---|---|---|
| <$10 | 4.21 | 5.61 | 5,657 | 13.11 |
| >=$10_<$20 | 7.92 | 10.57 | 22,424 | 51.98 |
| >=$20_<$40 | 25.17 | 33.57 | 4,738 | 10.98 |
| >=$40_<$60 | 34.06 | 45.43 | 5,759 | 13.35 |
| >=$60_<$100 | 53.66 | 71.58 | 3,629 | 8.41 |
| >=$100_<$200 | 79.86 | 106.53 | 931 | 2.16 |
| >=$200 | 199.16 | 265.65 | 4 | 0.01 |
Around 10.5% of beneficiaries of monthly cash-based transfers have received more than 50% of the value of the minimum expenditure basket for food. Notably, 13% of beneficiary households have received less than USD 10 per household per month. This underscores the importance of standardisation: beneficiaries have already received very different package amounts and there is a pressing need to collect information on whether cash transfers (and food baskets) have been designed to be full rations, half rations or are instead intended to be supplementary activities. This is key from a coordination standpoint as we cannot consider the food security needs of those who have only received supplementary transfers to have been covered.
Of the implementing partners of the Food Security Cluster, a total of 62 of them classified themselves as implementing partners within the 5Ws. They are fairly evenly split themselves between HRP indicators, with 36 contributing towards food and cash assistance and 39 contributing towards agriculture and other livelihood support. 34 partners have reached less than 10,000 unique beneficiaries and the median unique beneficiaries reached by partners is 6,118. Below are the top 10 partners by HRP indicator. As a side note, Zigway should be considered as a vendor/supplier of WFP, and not the implementing partner – some follow up with WFP will be necessary to rectify this.
| Partners HRP indicator1 |
|
Partners HRP indicator2 |
|
|
|---|---|---|---|---|
| MRCS | 640,223 | CESVI Foundation | 196,869 | |
| Open Data Myanmar (ODM) | 400,933 | Center for Social Integrity (CSI) | 84,427 | |
| Zigway | 223,478 | Helen Keller International | 57,287 | |
| Hlaingthayar Development Network | 204,275 | Action for Green Earth | 29,425 | |
| Urban Strength (US) | 201,732 | Action Contre la Faim | 23,128 | |
| World Vision Myanmar | 180,741 | People for People | 18,273 | |
| WFP | 110,235 | World Vision Myanmar | 18,040 | |
| Hlaingthayar Youth Network | 96,145 | Myanmar Heart Development Organization | 11,170 | |
| Myanmar Heart Development Organization | 70,664 | Da-Nu National Affairs organization (DNAO) | 9,266 | |
| Karuna Mission Social Solidarity | 70,014 | WFP | 8,061 |
Whilst there is quite a bit of variation in the number of beneficiaries reached, we can see that partners’ geographic footprints are – on the whole – quite limited. Only 8 partners have a presence in more than 10 townships, with only 13 being present in more than 5 townships. 78% of our partners (clustered along the bottom of the chart) are present in 5 or less townships. This distribution of partners is an impediment to a countrywide response and it is imperative to understand how best to incentivise partners to expand their footprints.
Food Security Cluster partners are not well-positioned to meet the needs of the 2022 population in need. Partners are largely concentrated in Kachin, Rakhine and Yangon, with only one partner present in Shan (East) and two in Tanintharyi.
Overall, 58% of townships, containing 46% of the 2022 PIN, do not have any partners present. This lack of nationwide coverage will be one of the most important constraints that the FSC will face in meeting the 2022 needs of vulnerable, food insecure persons and IDPs – and resolving this will necessitate both increasing partner coverage and finding new partners for the cluster.
The plot above shows the top 20 partners by number of beneficiaries reached in 2021, with the red line indicating July 2021, when the HRP addendum was approved and published. We can see that many, on the whole, the HRP addendum had a very large effect on the number of beneficiaries reached – most partners enacted a significant ramp up and reached the majority of beneficiaries after it was published. Exceptions to this include organisations such as CESVI, Helen Keller International, Save the Children and Myanmar Heart Development Organisation, who established most of their caseload prior to July 2021.
| implementing_partner_type | avg_beneficiaries | avg_townships | avg_states |
|---|---|---|---|
| INGO | 153,373 | 7.55 | 2.60 |
| NNGO | 110,421 | 3.10 | 1.21 |
| other | 73,975 | 2.00 | 1.00 |
| UN | 1,522,754 | 54.00 | 12.00 |
INGOs, on average, reached more beneficiaries across more townships than NNGOs, perhaps due to the generally tighter focus of several community-based organisations. There is only one agency in the “UN” category – WFP; the “other” category refers to two private limited companies which also implemented food security activities.
There are 72 combinations between reporting organisations and implementing partners, 23 of which are instances where the reporting organisation and the implementing partner are the same organisation; once these are filtered out, all the remaining implementing partners correspond to just 11 reporting organisations:
| reporting_organization | implementing_partners |
|---|---|
| WFP | 25 |
| FAO | 6 |
| Finn Church Aid | 4 |
| Save the Children | 4 |
| Cordaid | 2 |
| Mercy Corps | 2 |
| Trocaire | 2 |
| AVSI | 1 |
| Danish Refugee Council | 1 |
| Helvetas | 1 |
| Oxfam | 1 |
Regarding questions of membership, it would be safe to say that all partners who reported in the 5Ws – be they reporting organisations or implementing partners – in addition to strategic partners and partners who aid in analysis who are not represented in the 5Ws, are FSC partners. However, for this report, we have used implementing_partners for most of the analysis as, by their nature, reporting organisations do not have a field presence. As a side note, FAO has not classified itself as an implementing partner, having reported no activities that were directly implemented by them.
69% of the rows had the donor column filled; however, this only represents activities reaching 23% of all beneficiaries. Below is a table of the 10 donors (after organisations using their own resources) whose funding has reached the most beneficiaries and the number of townships their funding has been used in:
| donor | beneficiaries | pc_of_ben | townships |
|---|---|---|---|
| Organizational own funds | 191,006 | 5.86 | 36 |
| UNDP | 118,113 | 3.62 | 2 |
| humanitarian Assitance and resilience Programme | 87,502 | 2.68 | 7 |
| AICS | 63,986 | 1.96 | 5 |
| MHF | 61,056 | 1.87 | 11 |
| King Philanthropies | 57,287 | 1.76 | 7 |
| ECHO | 26,789 | 0.82 | 3 |
| FCDO | 23,282 | 0.71 | 3 |
| LIFT | 18,958 | 0.58 | 9 |
| European Union (EU) | 13,882 | 0.43 | 4 |
| HELVETAS | 13,851 | 0.42 | 6 |
Additionally, we also observe a number of errors, including cases where multiple donors have been combined into one row as well as numerous instances where UNDP, WFP, FAO and UN WOMEN were classified as donors as opposed to reporting organisations. Helvetas should also probably have reported under “organisations using their own funds”.
Currently, in the 5Ws, the vast majority of beneficiary diasaggregations have been backfilled from census data and do not, consequently, provide an accurate picture of the population that have been reached by Food Security interventions. It is not possible to determine how far reality diverges from what has been reported so far – meaning that we also cannot determine if there has been any bias in beneficiary selection and targetting. It is imperative to begin collecting disaggregated beneficiary data from partners.
It is entirely possible that partners are collecting this data – disaggregated beneficiary data is one of the most common data required for internal and external reporting – and that it is merely necessary to work with partners to wrangle their data into the 5W format. However, the capacities of partners to disaggregate beneficiary data should be investigated by the cluster and is an important issue that should be brought up in te next plenary session.
The states and regions in which we are working the most with IDPs are Bago (East), Kachin, Chin, Shan (North) and Kayah. Overall, 82.68% of beneficiaries are from the host/local community, 9.02% are stateless persons from Rakhine and 8.24% are IDPs. Returnees are the rarest type of beneficiary reached, forming only 0.07% of all beneficiaries reached. Each row in the table below shows the percentage of each beneficiary type within each state/region.
| state | Host/local Community | Internally Displaced | Returnees | Rakhine stateless | beneficiaries |
|---|---|---|---|---|---|
| Ayeyarwady | 100.00 | 99,481 | |||
| Bago (East) | 66.42 | 33.31 | 0.27 | 12,974 | |
| Chin | 7.35 | 92.65 | 17,005 | ||
| Kachin | 7.68 | 90.65 | 1.67 | 89,818 | |
| Kayah | 46.88 | 53.12 | 17,746 | ||
| Kayin | 67.37 | 32.63 | 68,108 | ||
| Magway | 99.03 | 0.97 | 96,767 | ||
| Mandalay | 100.00 | 143,526 | |||
| Mon | 92.50 | 5.88 | 1.62 | 48,181 | |
| Rakhine | 34.39 | 10.16 | 55.45 | 530,202 | |
| Sagaing | 25.29 | 74.71 | 31,985 | ||
| Shan (East) | 100.00 | 510 | |||
| Shan (North) | 26.44 | 73.56 | 73,103 | ||
| Shan (South) | 100.00 | 15,511 | |||
| Tanintharyi | 95.64 | 4.13 | 0.22 | 4,476 | |
| Yangon | 100.00 | 2,011,575 | |||
| Total | 82.68 | 8.24 | 0.07 | 9.02 |
Compared to only the 2021 HRP targets (as the IERP does not have breakdowns of the target by beneficiary type), we can see that whilst targets have been mostly exceeded, neither the targets for returnees/resettled in Kachin or Shan (North) nor targets for IDPs in Rakhine or Kayin have been met. Interestingly, for Rakhine, the targets for the host/local population have been greatly exceeded, perhaps indicating that once targets were met, all further allocations were targetted at the host/local communities. In Bago (East), Chin, Kayin and particularly Shan (North), the targets for IDPs have been greatly exceeded, in comparison to the 2021 HRP targets:
| state | host_local% | idp% | returnees% | rakhine_stateless% | total% |
|---|---|---|---|---|---|
| Bago (East) | 171.99 | 173.38 | |||
| Chin | 0.00 | 200.74 | 156.95 | ||
| Kachin | 88.67 | 110.36 | 32.88 | 104.30 | |
| Kayin | 168.08 | 196.98 | |||
| Rakhine | 409.86 | 32.71 | 105.75 | 108.83 | |
| Shan (North) | 135.56 | 751.31 | 0.00 | 400.17 | |
| Shan (South) | 0.00 | 0.00 |
Stateless persons from Rakhine have the largest average household sizes, with returnees having the largest variations in household size. With reference to the plot below, the thick bar in the middle of each box shows the average household size for each beneficiary type – this value is also shown in the text label below the line. The lower and upper borders of each box indicate the values for the 25th and 75th percentiles respectively. For instance, we can see that households at the 25th percentile of households in host/local communities have only four members and households that have around 5 members have more members than 75% of all the households in that group. Outliers are marked by dots. We note a lot of potential data entry errors where less than one person per household was reported.
Whilst the numbers of IDPs and Returnees reached did see significant increases after July 2021, we do not observe any evidence that this was the result of the HRP addendum, rather than the continuation of already existing plans. However, we do note a significant increase in the numbers of persons in the host/local community reached after July 2021 – 75% of all host/local community beneficiaries were reached after the publication of the HRP addendum. Conversely, the progress amongst state Rakhine persons slowed substantially after the publication of the addendum; as we have mentioned earlier, once targets were reached for stateless persons, additional allocations were directed at the host/local community – whether this was due to access issues or that the host/local community in Rakhine were evaluated to be as food insecure as the stateless population remains to be investigated.
| beneficiary_type | before_addendum | after_addendum | Total | %before | %after |
|---|---|---|---|---|---|
| Host/local Community | 667,103 | 2,028,907 | 2,696,010 | 24.74 | 75.26 |
| Rakhine stateless | 246,891 | 47,101 | 293,992 | 83.98 | 16.02 |
| Internally Displaced | 145,206 | 123,436 | 268,642 | 54.05 | 45.95 |
| Returnees | 1,046 | 1,278 | 2,324 | 45.01 | 54.99 |
| gap_months | locations | townships | beneficiaries | pc_of_ben |
|---|---|---|---|---|
| 0 | 283 | 35 | 457,448 | 51.48 |
| 1 | 51 | 21 | 73,704 | 8.29 |
| 2 | 122 | 22 | 63,397 | 7.13 |
| 3 | 406 | 12 | 236,978 | 26.67 |
| 4 | 8 | 5 | 8,485 | 0.95 |
| 5 | 9 | 5 | 28,195 | 3.17 |
| 8 | 1 | 1 | 20,393 | 2.29 |
49% of beneficiaries experienced gaps or delays in monthly programming, with the most common delay being 3 months. The 8-month delay was the provision of monthly food baskets in Buthidaung, where distributions only occurred in February and November 2021. The 5-month delays were all from locations in Rakhine and Kachin. Overall, gaps in monthly programming were experienced in 39 townships, with the majority orginating from Kachin, Ayeyarwady and Rakhine.
There are 276 entries coded as being implemented on a monthly basis that have not recurred – that is, they have only been implemented once: we should check with partners if these are merely the first instances, or if there have been issues with access, security or funding or if they are errors in data entry .
The table below shows activities which have been implemented for 6 months or more, the number of locations they were implemented in and the number of unique beneficiaries reached by activities meeting these criteria. The possibility of joint monitoring – or at least the joint review and analysis of monitoring data – will be explored, in consultation with these partners. The rationale being that 6 months of implementation should be a long enough period of time to make impact monitoring feasible; additionally, joint monitoring will be further facilitated by the similarity of these activities, almost all of which are recurrent cash transfers or distributions of food baskets.
| activity | partners | locations | beneficiaries |
|---|---|---|---|
| Provide monthly cash-based transfers | 7 | 231 | 194,400 |
| Provide monthly food baskets | 7 | 44 | 147,819 |
| Provide technical training | 2 | 413 | 57,887 |
| Provide crops & vegetables kits | 1 | 406 | 57,287 |
| Provide support for income generation | 1 | 407 | 57,287 |
| Cash for Work / Food for Assets | 1 | 1 | 245 |
These are the partners who have implemented monthly food baskets and monthly cash-based transfers for more than 6 months:
| implementing_partners | Provide monthly cash-based transfers | Provide monthly food baskets |
|---|---|---|
| Karuna Mission Social Solidarity | 51,702 | 85 |
| Myanmar Heart Development Organization | 30,185 | 57,638 |
| People for People | 23,982 | |
| Plan International | 37,657 | |
| Save the Children | 144 | |
| WFP | 39,192 | 42,002 |
| World Vision Myanmar | 11,538 | 19,559 |
| Action for Green Earth | 18,755 | |
| People Hope Community Development (PHCD) | 8,872 | |
| Together for Sustainable Development | 908 |
Communicate to partners that Yangon is severely oversubscribed in comparison to the rest of the country, above all in the townships of Hlaingtharya, Shwepyithar, Dagon Myothit (Seikkan), Dala and North Okkalapa.
Collect existing intervention packages from partners in order to begin the process of standardisation and to support the review of food baskets for their caloric and nutritional value. Perform additional analysis to understand if beneficiaries in close proximity to each other have received widely divergent package values. Additionally, speak with partners to understand why cash transfer values vary even within the same activity implemented by the same partner.
Revisit areas which have only received smaller supplementary transfers – a transfer of around USD 10 per household per month cannot be considered to have covered the food security needs for that area – other partners may be necessary to cover the gap.
Advocate for the expansion of partners’ geographic footprints to reach the remaining 179 townships which have yet to benefit from any FSC activities. The effects of the current crisis in Myanmar have not been determined by an epicentre or a stormpath and there is no programmatic rationale for the response to be so uneven. This advocacy should be targetted at the ICCG, Cluster partners and at donors.
Collect 5W data from other clusters so that multi-sector coverage may be reviewed. Clean and process conflict data so that it may be cross-referenced with partners’ coverage. Share raw data with other Clusters to improve coordination.
Work with partners to determine their current capacities to submit age and sex-disaggregated beneficiary data. Develop a workplan to ensure that they can meet reporting requirements.
Solicit monitoring reports from partners and explore the possibility of joint monitoring.
Revise the 5W template – in consultation with partners – in order to address the data collection issues identified.
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